/*
 * Copyright (C) 2013 The Guava Authors
 *
 * Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
 * in compliance with the License. You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software distributed under the License
 * is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
 * or implied. See the License for the specific language governing permissions and limitations under
 * the License.
 */

package com.google.common.math;

import static com.google.common.base.Preconditions.checkArgument;
import static com.google.common.truth.Truth.assertThat;
import static java.lang.Double.NEGATIVE_INFINITY;
import static java.lang.Double.NaN;
import static java.lang.Double.POSITIVE_INFINITY;
import static org.junit.Assert.fail;

import com.google.common.base.Predicates;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.Iterables;
import com.google.common.collect.Lists;
import com.google.common.primitives.Doubles;
import com.google.common.primitives.Ints;
import java.math.BigInteger;
import java.util.List;

/**
 * Inputs, expected outputs, and helper methods for tests of {@link StatsAccumulator},
 * {@link Stats}, {@link PairedStatsAccumulator}, and {@link PairedStats}.
 *
 * @author Pete Gillin
 */
class StatsTesting {

    static final double ALLOWED_ERROR = 1e-10;

    // Inputs and their statistics:

    static final double ONE_VALUE = 12.34;

    static final double OTHER_ONE_VALUE = -56.78;

    static final ImmutableList<Double> TWO_VALUES = ImmutableList.of(12.34, -56.78);
    static final double TWO_VALUES_MEAN = (12.34 - 56.78) / 2;
    static final double TWO_VALUES_SUM_OF_SQUARES_OF_DELTAS = (12.34 - TWO_VALUES_MEAN) * (12.34 - TWO_VALUES_MEAN)
            + (-56.78 - TWO_VALUES_MEAN) * (-56.78 - TWO_VALUES_MEAN);
    static final double TWO_VALUES_MAX = 12.34;
    static final double TWO_VALUES_MIN = -56.78;

    static final ImmutableList<Double> OTHER_TWO_VALUES = ImmutableList.of(123.456, -789.012);
    static final double OTHER_TWO_VALUES_MEAN = (123.456 - 789.012) / 2;
    static final double TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS =
            (12.34 - TWO_VALUES_MEAN) * (123.456 - OTHER_TWO_VALUES_MEAN)
                    + (-56.78 - TWO_VALUES_MEAN) * (-789.012 - OTHER_TWO_VALUES_MEAN);

    /**
     * Helper class for testing with non-finite values. {@link #ALL_MANY_VALUES} gives a number
     * instances with many combinations of finite and non-finite values. All have
     * {@link #MANY_VALUES_COUNT} values. If all the values are finite then the mean is
     * {@link #MANY_VALUES_MEAN} and the sum-of-squares-of-deltas is
     * {@link #MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS}. The smallest and largest finite values are
     * always {@link #MANY_VALUES_MIN} and {@link #MANY_VALUES_MAX}, although setting non-finite
     * values will change the true min and max.
     */
    static class ManyValues {

        private final ImmutableList<Double> values;

        ManyValues(double[] values) {
            this.values = ImmutableList.copyOf(Doubles.asList(values));
        }

        ImmutableList<Double> asIterable() {
            return values;
        }

        double[] asArray() {
            return Doubles.toArray(values);
        }

        boolean hasAnyPositiveInfinity() {
            return Iterables.any(values, Predicates.equalTo(POSITIVE_INFINITY));
        }

        boolean hasAnyNegativeInfinity() {
            return Iterables.any(values, Predicates.equalTo(NEGATIVE_INFINITY));
        }

        boolean hasAnyNaN() {
            return Iterables.any(values, Predicates.equalTo(NaN));
        }

        boolean hasAnyNonFinite() {
            return hasAnyPositiveInfinity() || hasAnyNegativeInfinity() || hasAnyNaN();
        }

        @Override
        public String toString() {
            return values.toString();
        }

        private static ImmutableList<ManyValues> createAll() {
            ImmutableList.Builder<ManyValues> builder = ImmutableList.builder();
            double[] values = new double[5];
            for (double first : ImmutableList.of(1.1, POSITIVE_INFINITY, NEGATIVE_INFINITY, NaN)) {
                values[0] = first;
                values[1] = -44.44;
                for (double third : ImmutableList.of(33.33, POSITIVE_INFINITY, NEGATIVE_INFINITY, NaN)) {
                    values[2] = third;
                    values[3] = 555.555;
                    for (double fifth : ImmutableList.of(-2.2, POSITIVE_INFINITY, NEGATIVE_INFINITY, NaN)) {
                        values[4] = fifth;
                        builder.add(new ManyValues(values));
                    }
                }
            }
            return builder.build();
        }
    }

    static final Iterable<ManyValues> ALL_MANY_VALUES = ManyValues.createAll();

    static final ImmutableList<Double> MANY_VALUES = ImmutableList.of(1.1, -44.44, 33.33, 555.555, -2.2);
    static final int MANY_VALUES_COUNT = 5;
    static final double MANY_VALUES_MEAN = (1.1 - 44.44 + 33.33 + 555.555 - 2.2) / 5;
    static final double MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS = (1.1 - MANY_VALUES_MEAN) * (1.1 - MANY_VALUES_MEAN)
            + (-44.44 - MANY_VALUES_MEAN) * (-44.44 - MANY_VALUES_MEAN)
            + (33.33 - MANY_VALUES_MEAN) * (33.33 - MANY_VALUES_MEAN)
            + (555.555 - MANY_VALUES_MEAN) * (555.555 - MANY_VALUES_MEAN)
            + (-2.2 - MANY_VALUES_MEAN) * (-2.2 - MANY_VALUES_MEAN);
    static final double MANY_VALUES_MAX = 555.555;
    static final double MANY_VALUES_MIN = -44.44;

    // Doubles which will overflow if summed:
    static final double[] LARGE_VALUES = {Double.MAX_VALUE, Double.MAX_VALUE / 2.0};
    static final double LARGE_VALUES_MEAN = 0.75 * Double.MAX_VALUE;

    static final ImmutableList<Double> OTHER_MANY_VALUES = ImmutableList.of(1.11, -2.22, 33.3333, -44.4444, 555.555555);
    static final int OTHER_MANY_VALUES_COUNT = 5;
    static final double OTHER_MANY_VALUES_MEAN = (1.11 - 2.22 + 33.3333 - 44.4444 + 555.555555) / 5;

    static final double MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS =
            (1.1 - MANY_VALUES_MEAN) * (1.11 - OTHER_MANY_VALUES_MEAN)
                    + (-44.44 - MANY_VALUES_MEAN) * (-2.22 - OTHER_MANY_VALUES_MEAN)
                    + (33.33 - MANY_VALUES_MEAN) * (33.3333 - OTHER_MANY_VALUES_MEAN)
                    + (555.555 - MANY_VALUES_MEAN) * (-44.4444 - OTHER_MANY_VALUES_MEAN)
                    + (-2.2 - MANY_VALUES_MEAN) * (555.555555 - OTHER_MANY_VALUES_MEAN);

    static final ImmutableList<Integer> INTEGER_MANY_VALUES = ImmutableList.of(11, -22, 3333, -4444, 555555);
    static final int INTEGER_MANY_VALUES_COUNT = 5;
    static final double INTEGER_MANY_VALUES_MEAN = (11.0 - 22.0 + 3333.0 - 4444.0 + 555555.0) / 5;
    static final double INTEGER_MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS =
            (11.0 - INTEGER_MANY_VALUES_MEAN) * (11.0 - INTEGER_MANY_VALUES_MEAN)
                    + (-22.0 - INTEGER_MANY_VALUES_MEAN) * (-22.0 - INTEGER_MANY_VALUES_MEAN)
                    + (3333.0 - INTEGER_MANY_VALUES_MEAN) * (3333.0 - INTEGER_MANY_VALUES_MEAN)
                    + (-4444.0 - INTEGER_MANY_VALUES_MEAN) * (-4444.0 - INTEGER_MANY_VALUES_MEAN)
                    + (555555.0 - INTEGER_MANY_VALUES_MEAN) * (555555.0 - INTEGER_MANY_VALUES_MEAN);
    static final double INTEGER_MANY_VALUES_MAX = 555555.0;
    static final double INTEGER_MANY_VALUES_MIN = -4444.0;

    // Integers which will overflow if summed (using integer arithmetic):
    static final int[] LARGE_INTEGER_VALUES = {Integer.MAX_VALUE, Integer.MAX_VALUE / 2};
    static final double LARGE_INTEGER_VALUES_MEAN = BigInteger.valueOf(Integer.MAX_VALUE)
            .multiply(BigInteger.valueOf(3L)).divide(BigInteger.valueOf(4L)).doubleValue();
    static final double LARGE_INTEGER_VALUES_POPULATION_VARIANCE = BigInteger.valueOf(Integer.MAX_VALUE)
            .multiply(BigInteger.valueOf(Integer.MAX_VALUE)).divide(BigInteger.valueOf(16L)).doubleValue();

    static final ImmutableList<Long> LONG_MANY_VALUES =
            ImmutableList.of(1111L, -2222L, 33333333L, -44444444L, 5555555555L);
    static final int LONG_MANY_VALUES_COUNT = 5;
    static final double LONG_MANY_VALUES_MEAN = (1111.0 - 2222.0 + 33333333.0 - 44444444.0 + 5555555555.0) / 5;
    static final double LONG_MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS =
            (1111.0 - LONG_MANY_VALUES_MEAN) * (1111.0 - LONG_MANY_VALUES_MEAN)
                    + (-2222.0 - LONG_MANY_VALUES_MEAN) * (-2222.0 - LONG_MANY_VALUES_MEAN)
                    + (33333333.0 - LONG_MANY_VALUES_MEAN) * (33333333.0 - LONG_MANY_VALUES_MEAN)
                    + (-44444444.0 - LONG_MANY_VALUES_MEAN) * (-44444444.0 - LONG_MANY_VALUES_MEAN)
                    + (5555555555.0 - LONG_MANY_VALUES_MEAN) * (5555555555.0 - LONG_MANY_VALUES_MEAN);
    static final double LONG_MANY_VALUES_MAX = 5555555555.0;
    static final double LONG_MANY_VALUES_MIN = -44444444.0;

    // Longs which will overflow if summed (using long arithmetic):
    static final long[] LARGE_LONG_VALUES = {Long.MAX_VALUE, Long.MAX_VALUE / 2};
    static final double LARGE_LONG_VALUES_MEAN = BigInteger.valueOf(Long.MAX_VALUE).multiply(BigInteger.valueOf(3L))
            .divide(BigInteger.valueOf(4L)).doubleValue();
    static final double LARGE_LONG_VALUES_POPULATION_VARIANCE = BigInteger.valueOf(Long.MAX_VALUE)
            .multiply(BigInteger.valueOf(Long.MAX_VALUE)).divide(BigInteger.valueOf(16L)).doubleValue();

    // Stats instances:

    static final Stats EMPTY_STATS_VARARGS = Stats.of();
    static final Stats EMPTY_STATS_ITERABLE = Stats.of(ImmutableList.<Double>of());
    static final Stats ONE_VALUE_STATS = Stats.of(ONE_VALUE);
    static final Stats OTHER_ONE_VALUE_STATS = Stats.of(OTHER_ONE_VALUE);
    static final Stats TWO_VALUES_STATS = Stats.of(TWO_VALUES);
    static final Stats OTHER_TWO_VALUES_STATS = Stats.of(OTHER_TWO_VALUES);
    static final Stats MANY_VALUES_STATS_VARARGS = Stats.of(1.1, -44.44, 33.33, 555.555, -2.2);
    static final Stats MANY_VALUES_STATS_ITERABLE = Stats.of(MANY_VALUES);
    static final Stats MANY_VALUES_STATS_ITERATOR = Stats.of(MANY_VALUES.iterator());
    static final Stats MANY_VALUES_STATS_SNAPSHOT;
    static final Stats LARGE_VALUES_STATS = Stats.of(LARGE_VALUES);
    static final Stats OTHER_MANY_VALUES_STATS = Stats.of(OTHER_MANY_VALUES);
    static final Stats INTEGER_MANY_VALUES_STATS_VARARGS = Stats.of(Ints.toArray(INTEGER_MANY_VALUES));
    static final Stats INTEGER_MANY_VALUES_STATS_ITERABLE = Stats.of(INTEGER_MANY_VALUES);
    static final Stats LARGE_INTEGER_VALUES_STATS = Stats.of(LARGE_INTEGER_VALUES);
    static final Stats LONG_MANY_VALUES_STATS_ITERATOR = Stats.of(LONG_MANY_VALUES.iterator());
    static final Stats LONG_MANY_VALUES_STATS_SNAPSHOT;
    static final Stats LARGE_LONG_VALUES_STATS = Stats.of(LARGE_LONG_VALUES);

    static {
        StatsAccumulator accumulator = new StatsAccumulator();
        accumulator.addAll(MANY_VALUES);
        MANY_VALUES_STATS_SNAPSHOT = accumulator.snapshot();
        accumulator.add(999.999); // should do nothing to the snapshot
    }

    static {
        StatsAccumulator accumulator = new StatsAccumulator();
        accumulator.addAll(LONG_MANY_VALUES);
        LONG_MANY_VALUES_STATS_SNAPSHOT = accumulator.snapshot();
    }

    static final List<Stats> ALL_STATS =
            ImmutableList.of(EMPTY_STATS_VARARGS, EMPTY_STATS_ITERABLE, ONE_VALUE_STATS, OTHER_ONE_VALUE_STATS,
                    TWO_VALUES_STATS, OTHER_TWO_VALUES_STATS, MANY_VALUES_STATS_VARARGS, MANY_VALUES_STATS_ITERABLE,
                    MANY_VALUES_STATS_ITERATOR, MANY_VALUES_STATS_SNAPSHOT, LARGE_VALUES_STATS, OTHER_MANY_VALUES_STATS,
                    INTEGER_MANY_VALUES_STATS_VARARGS, INTEGER_MANY_VALUES_STATS_ITERABLE, LARGE_INTEGER_VALUES_STATS,
                    LONG_MANY_VALUES_STATS_ITERATOR, LONG_MANY_VALUES_STATS_SNAPSHOT, LARGE_LONG_VALUES_STATS);

    // PairedStats instances:

    static final PairedStats EMPTY_PAIRED_STATS =
            createPairedStatsOf(ImmutableList.<Double>of(), ImmutableList.<Double>of());
    static final PairedStats ONE_VALUE_PAIRED_STATS =
            createPairedStatsOf(ImmutableList.of(ONE_VALUE), ImmutableList.of(OTHER_ONE_VALUE));
    static final PairedStats TWO_VALUES_PAIRED_STATS = createPairedStatsOf(TWO_VALUES, OTHER_TWO_VALUES);
    static final PairedStats MANY_VALUES_PAIRED_STATS;
    static final PairedStats DUPLICATE_MANY_VALUES_PAIRED_STATS = createPairedStatsOf(MANY_VALUES, OTHER_MANY_VALUES);
    static final PairedStats HORIZONTAL_VALUES_PAIRED_STATS;
    static final PairedStats VERTICAL_VALUES_PAIRED_STATS;
    static final PairedStats CONSTANT_VALUES_PAIRED_STATS;

    static {
        PairedStatsAccumulator accumulator = createFilledPairedStatsAccumulator(MANY_VALUES, OTHER_MANY_VALUES);
        MANY_VALUES_PAIRED_STATS = accumulator.snapshot();
        accumulator.add(99.99, 9999.9999); // should do nothing to the snapshot
    }

    static {
        PairedStatsAccumulator accumulator = new PairedStatsAccumulator();
        for (double x : MANY_VALUES) {
            accumulator.add(x, OTHER_ONE_VALUE);
        }
        HORIZONTAL_VALUES_PAIRED_STATS = accumulator.snapshot();
    }

    static {
        PairedStatsAccumulator accumulator = new PairedStatsAccumulator();
        for (double y : OTHER_MANY_VALUES) {
            accumulator.add(ONE_VALUE, y);
        }
        VERTICAL_VALUES_PAIRED_STATS = accumulator.snapshot();
    }

    static {
        PairedStatsAccumulator accumulator = new PairedStatsAccumulator();
        for (int i = 0; i < MANY_VALUES_COUNT; ++i) {
            accumulator.add(ONE_VALUE, OTHER_ONE_VALUE);
        }
        CONSTANT_VALUES_PAIRED_STATS = accumulator.snapshot();
    }

    static final List<PairedStats> ALL_PAIRED_STATS = ImmutableList.of(EMPTY_PAIRED_STATS, ONE_VALUE_PAIRED_STATS,
            TWO_VALUES_PAIRED_STATS, MANY_VALUES_PAIRED_STATS, DUPLICATE_MANY_VALUES_PAIRED_STATS,
            HORIZONTAL_VALUES_PAIRED_STATS, VERTICAL_VALUES_PAIRED_STATS, CONSTANT_VALUES_PAIRED_STATS);

    // Helper methods:

    static void assertStatsApproxEqual(Stats expectedStats, Stats actualStats) {
        assertThat(actualStats.count()).isEqualTo(expectedStats.count());
        if (expectedStats.count() == 0) {
            try {
                actualStats.mean();
                fail("Expected IllegalStateException");
            } catch (IllegalStateException expected) {
            }
            try {
                actualStats.populationVariance();
                fail("Expected IllegalStateException");
            } catch (IllegalStateException expected) {
            }
            try {
                actualStats.min();
                fail("Expected IllegalStateException");
            } catch (IllegalStateException expected) {
            }
            try {
                actualStats.max();
                fail("Expected IllegalStateException");
            } catch (IllegalStateException expected) {
            }
        } else if (expectedStats.count() == 1) {
            assertThat(actualStats.mean()).isWithin(ALLOWED_ERROR).of(expectedStats.mean());
            assertThat(actualStats.populationVariance()).isWithin(0.0).of(0.0);
            assertThat(actualStats.min()).isWithin(ALLOWED_ERROR).of(expectedStats.min());
            assertThat(actualStats.max()).isWithin(ALLOWED_ERROR).of(expectedStats.max());
        } else {
            assertThat(actualStats.mean()).isWithin(ALLOWED_ERROR).of(expectedStats.mean());
            assertThat(actualStats.populationVariance()).isWithin(ALLOWED_ERROR).of(expectedStats.populationVariance());
            assertThat(actualStats.min()).isWithin(ALLOWED_ERROR).of(expectedStats.min());
            assertThat(actualStats.max()).isWithin(ALLOWED_ERROR).of(expectedStats.max());
        }
    }

    /**
     * Asserts that {@code transformation} is diagonal (i.e. neither horizontal or vertical) and
     * passes through both {@code (x1, y1)} and {@code (x1 + xDelta, y1 + yDelta)}. Includes
     * assertions about all the public instance methods of {@link LinearTransformation} (on both
     * {@code transformation} and its inverse). Since the transformation is expected to be diagonal,
     * neither {@code xDelta} nor {@code yDelta} may be zero.
     */
    static void assertDiagonalLinearTransformation(LinearTransformation transformation, double x1, double y1,
            double xDelta, double yDelta) {
        checkArgument(xDelta != 0.0);
        checkArgument(yDelta != 0.0);
        assertThat(transformation.isHorizontal()).isFalse();
        assertThat(transformation.isVertical()).isFalse();
        assertThat(transformation.inverse().isHorizontal()).isFalse();
        assertThat(transformation.inverse().isVertical()).isFalse();
        assertThat(transformation.transform(x1)).isWithin(ALLOWED_ERROR).of(y1);
        assertThat(transformation.transform(x1 + xDelta)).isWithin(ALLOWED_ERROR).of(y1 + yDelta);
        assertThat(transformation.inverse().transform(y1)).isWithin(ALLOWED_ERROR).of(x1);
        assertThat(transformation.inverse().transform(y1 + yDelta)).isWithin(ALLOWED_ERROR).of(x1 + xDelta);
        assertThat(transformation.slope()).isWithin(ALLOWED_ERROR).of(yDelta / xDelta);
        assertThat(transformation.inverse().slope()).isWithin(ALLOWED_ERROR).of(xDelta / yDelta);
        assertThat(transformation.inverse()).isSameAs(transformation.inverse());
        assertThat(transformation.inverse().inverse()).isSameAs(transformation);
    }

    /**
     * Asserts that {@code transformation} is horizontal with the given value of {@code y}. Includes
     * assertions about all the public instance methods of {@link LinearTransformation}, including
     * an assertion that {@link LinearTransformation#transform} and
     * {@link LinearTransformation#slope} on its inverse throws as expected.
     */
    static void assertHorizontalLinearTransformation(LinearTransformation transformation, double y) {
        assertThat(transformation.isHorizontal()).isTrue();
        assertThat(transformation.isVertical()).isFalse();
        assertThat(transformation.inverse().isHorizontal()).isFalse();
        assertThat(transformation.inverse().isVertical()).isTrue();
        assertThat(transformation.transform(-1.0)).isWithin(ALLOWED_ERROR).of(y);
        assertThat(transformation.transform(1.0)).isWithin(ALLOWED_ERROR).of(y);
        try {
            transformation.inverse().transform(0.0);
            fail("Expected IllegalStateException");
        } catch (IllegalStateException expected) {
        }
        assertThat(transformation.slope()).isWithin(ALLOWED_ERROR).of(0.0);
        try {
            transformation.inverse().slope();
            fail("Expected IllegalStateException");
        } catch (IllegalStateException expected) {
        }
        assertThat(transformation.inverse()).isSameAs(transformation.inverse());
        assertThat(transformation.inverse().inverse()).isSameAs(transformation);
    }

    /**
     * Asserts that {@code transformation} is vertical with the given value of {@code x}. Includes
     * assertions about all the public instance methods of {@link LinearTransformation}, including
     * assertions that {@link LinearTransformation#slope} and {@link LinearTransformation#transform}
     * throw as expected.
     */
    static void assertVerticalLinearTransformation(LinearTransformation transformation, double x) {
        assertThat(transformation.isHorizontal()).isFalse();
        assertThat(transformation.isVertical()).isTrue();
        assertThat(transformation.inverse().isHorizontal()).isTrue();
        assertThat(transformation.inverse().isVertical()).isFalse();
        try {
            transformation.transform(0.0);
            fail("Expected IllegalStateException");
        } catch (IllegalStateException expected) {
        }
        assertThat(transformation.inverse().transform(-1.0)).isWithin(ALLOWED_ERROR).of(x);
        assertThat(transformation.inverse().transform(1.0)).isWithin(ALLOWED_ERROR).of(x);
        try {
            transformation.slope();
            fail("Expected IllegalStateException");
        } catch (IllegalStateException expected) {
        }
        assertThat(transformation.inverse().slope()).isWithin(ALLOWED_ERROR).of(0.0);
        assertThat(transformation.inverse()).isSameAs(transformation.inverse());
        assertThat(transformation.inverse().inverse()).isSameAs(transformation);
    }

    /**
     * Asserts that {@code transformation} behaves as expected for
     * {@link LinearTransformation#forNaN}.
     */
    static void assertLinearTransformationNaN(LinearTransformation transformation) {
        assertThat(transformation.isHorizontal()).isFalse();
        assertThat(transformation.isVertical()).isFalse();
        assertThat(transformation.slope()).isNaN();
        assertThat(transformation.transform(0.0)).isNaN();
        assertThat(transformation.inverse()).isSameAs(transformation);
    }

    /**
     * Creates a {@link PairedStats} from with the given lists of {@code x} and {@code y} values,
     * which must be of the same size.
     */
    static PairedStats createPairedStatsOf(List<Double> xValues, List<Double> yValues) {
        return createFilledPairedStatsAccumulator(xValues, yValues).snapshot();
    }

    /**
     * Creates a {@link PairedStatsAccumulator} filled with the given lists of {@code x} and
     * {@code y} values, which must be of the same size.
     */
    static PairedStatsAccumulator createFilledPairedStatsAccumulator(List<Double> xValues, List<Double> yValues) {
        checkArgument(xValues.size() == yValues.size());
        PairedStatsAccumulator accumulator = new PairedStatsAccumulator();
        for (int index = 0; index < xValues.size(); index++) {
            accumulator.add(xValues.get(index), yValues.get(index));
        }
        return accumulator;
    }

    /**
     * Creates a {@link PairedStatsAccumulator} filled with the given lists of {@code x} and
     * {@code y} values, which must be of the same size, added in groups of {@code partitionSize}
     * using {@link PairedStatsAccumulator#addAll(PairedStats)}.
     */
    static PairedStatsAccumulator createPartitionedFilledPairedStatsAccumulator(List<Double> xValues,
            List<Double> yValues, int partitionSize) {
        checkArgument(xValues.size() == yValues.size());
        checkArgument(partitionSize > 0);
        PairedStatsAccumulator accumulator = new PairedStatsAccumulator();
        List<List<Double>> xPartitions = Lists.partition(xValues, partitionSize);
        List<List<Double>> yPartitions = Lists.partition(yValues, partitionSize);
        for (int index = 0; index < xPartitions.size(); index++) {
            accumulator.addAll(createPairedStatsOf(xPartitions.get(index), yPartitions.get(index)));
        }
        return accumulator;
    }

    private StatsTesting() {}
}
